A price that can be charged for advertising time during a media presentation is principally affected by a size of a potential viewing audience of the media event or show, as well as the demographics of the potential audience. It is generally recognized that a large audience will view significant sporting events (e.g., The Superbowl, World Cup soccer, etc.). However, knowledge of the audience size for other types of televised events or shows is more difficult to ascertain.
Typically, recorded past historical media consumption (e.g., television viewing, radio listening, etc.) is used to estimate future media consumption. FIG. 1 illustrates a prior-art example electronic media rating system 100 that measures viewership for media events or shows displayed on an information presenting device such as a television 105. To measure the viewership, the example electronic media rating system 100 includes a meter 110 (e.g., the Nielsen People Meter™ from Nielsen Media Research®) that records events or shows viewed by an audience member 115. In a known example, the meter 110 determines which televised events or shows are viewed by the audience member 115 by receiving signals from a remote control 120 that the audience member 115 uses to select events or shows. The meter 110 records and stores a list of tuned channels and times. The list is subsequently processed (together with lists gathered from other meters (not shown)) by, for example, compiling the gathered data against a schedule of programs to identify the tuned program and to determine statistics that characterize the viewership for individual televised events, individual televised shows, portions of days, portions of weeks, etc.
For locations in which more than one potential audience member may be present, the meter 110 can, in addition to recording the selected events and shows, record which audience member(s) were present during a selected event or show. The meter 110 can determine a presence of the audience member 115 by, for example, receiving signals from the remote control 120, or another remote device, that identify the audience member 115. For example, the audience member 115 could press one or more buttons on the remote 120 or directly on the meter 110 to identify themselves. In a known example, the meter 110 occasionally prompts the audience member 115 to signal their identification.
In some known examples, the meter 110 uses image recognition techniques to detect the presence of the audience member(s) 115. To perform the image recognition techniques, the meter 110 includes an image processor 130 that is responsive to visible light reflected off of the audience member(s) 115. The visible light might be created by the television 105 or by another visible light source 135 (e.g., a lamp, a light fixture, a window, a candle, etc.) present in a room. Using one or a variety of well-known techniques, the image processor 130 captures signals representative of the reflected light and applies appropriate signal processing to the captured signals to identify a number of audience members present. In some examples, the image processor 130 may be capable to distinguish the audience member(s) 115 such that the identities of the audience member(s) 115 can be electronically determined and recorded.
The signal capture and processing performed by the image processor 130 is significantly complicated in circumstances when the audience member(s) 115 are viewing an information presenting device such as a television 105 in a darkened room. Such circumstances can increase noise present in the captured signals, cause image contrast problems, increase shadows (e.g., shadows caused by a single non-diffused light source), etc. Further, scene changes during the televised event or show can cause significant variations in intensity of the reflected light. All of these conditions can reduce the effectiveness and accuracy of audience member detection and identification performed by the image processor 130.
As discussed above, the accuracy of image recognition based audience member detection and identification is typically dependent upon the quantity and quality of light present in the room being monitored. However, it is undesirable and impractical that the prior-art example electronic media rating system 100 either require the audience member(s) 115 to watch television with lights turned on, or watch with a specific arrangement of visible light sources to improved the effectiveness of the image recognition system. Such requirements could significantly reduce compliance of the participating audience member(s) 115, and could potentially reduce the number of willing participants in media exposure studies, thereby reducing the statistical accuracy of resultant media exposure ratings.
It is well known in photography, that indirect illumination provides illumination that is more uniform (i.e., substantially equal illumination spread across an area) and less prone to wash out details (i.e., to cause strong highlights that obscure details) in a scene being photographed.